Papers by Ruochang Li
HEAL: Hybrid Enhancement with LLM-based Agents for Text-attributed Hypergraph Self-supervised Representation Learning (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Existing approaches to enhance text-attributed hypergraph self-supervised learning are limited by label scarcity. |
| Approach: | They propose a data-centric approach that leverages large language models to enhance hypergraph self-supervised learning by integrating hyperedges into a self-representation framework. |
| Outcome: | The proposed approach generates informative nodes and hyperedges through multi-round interaction with LLM-based agents. |